Introducing AI to a small team

If you're curious about AI but not sure where it fits, or a little wary of it, you're not alone. Just under 3 in 10 UK businesses with fewer than ten staff use any kind of AI so far, and one of the reasons businesses give most often for holding back is simply not having the know-how. This guide is for that gap: where AI can take some of the load off a small team, where to be careful, and how to introduce it so people feel comfortable rather than worried.

Where it can help

AI is at its most useful on the everyday tasks that take time but don't need your judgement every step of the way.

First drafts. The thank-you letter to volunteers, the reply to a customer enquiry, the update for a funder, the social post about a finished job. In a study published in Science, people given everyday writing tasks took about 40% less time with AI, and their work was rated higher. The tasks didn't depend on precise facts, which is exactly why a person still reads and checks the result.

Helping newer colleagues. In a study of 5,000 customer support staff, AI helped the least experienced the most: people two months into the job, working with AI, performed as well as colleagues with six months' experience working without it. For a small team, that can mean a new starter or volunteer gets confident sooner, without taking up everyone else's time.

Answering "how do we…?" Set up with your own policies, procedures and templates, AI can answer everyday questions from your own information: where a form goes, what the policy on something is, which template to use.

Summarising. A long document, a long email thread, a set of meeting notes, turned into something short you can act on. You go back to the original for anything that matters.

Where to be careful

It can be confidently wrong. AI sometimes fills gaps with answers that sound right but aren't. Giving it your own documents helps a great deal, but doesn't remove the problem completely: Stanford researchers found that specialist tools built this way for lawyers still gave wrong or misleading answers between 17% and 33% of the time. So a person always checks.

Decisions stay with people. It can set out options and draft a recommendation. A person decides.

Personal and confidential information. The National Cyber Security Centre advises not to put sensitive information into public AI tools. Agree which tools and accounts your team uses, and keep anything confidential out of the rest.

Introducing it so people feel comfortable

Start with something people would be glad to hand over. Ask the team which repetitive task they'd most like help with, and start there. "Here's how it drafts our renewal reminders" is far more useful than a general demonstration.

Set it up around your own documents. A general tool knows nothing about your organisation. Given your policies, templates and the way you write, it becomes useful much more quickly. This is most of the setup work, and most of the value.

Make it clear people are welcome to use it. It sounds obvious, but it matters. In a study of 25,000 workers in Denmark, people whose employer encouraged AI use were far more likely to use it: an estimated 83%, compared with 47% where there was no encouragement.

Agree a few simple rules and write them down. For example:

1. A person checks everything before it goes anywhere.
2. Only agreed tools and accounts are used for work, and nothing confidential goes anywhere else.
3. If it gets something wrong, fix the document it drew on, so it doesn't happen again.
4. It's here to take repetitive work off people, not to replace them. (Only make this promise if it's true for your organisation.)

Talk about the worry. Some people will wonder what AI means for their job. It helps to say plainly why you're introducing it. The evidence so far is reassuring: only around 6% of UK businesses with ten or more staff that use AI say it has reduced their headcount, and a large study in Denmark found no effect on people's earnings or hours.

Learn together. A relaxed session with real examples, including what it looks like when it gets things wrong, followed by real tasks with someone on hand to help for the first couple of weeks.

What "comfortable" looks like

A team that's comfortable with AI uses it the way they use a spreadsheet or email: for the jobs it's good at, without fuss. They know what to hand it, they check what comes back, and they know when it isn't worth it. That comes from a few weeks of using it on real work, at your own pace, not from a single training day.

Common questions

Which AI tool should we use?

Usually the one that fits with what you already use and pay for, and that you are comfortable with on privacy. How it is set up matters more than which brand it is.

Is our data safe?

With a business account, most major providers state that they do not use your organisation's data to train their models by default; check the terms for the tool you choose. The bigger risk is people using free or personal accounts, which may not offer the same protection. That is why it helps to agree which tools and accounts are approved, and to keep personal and confidential information out of anything else.

How much does it cost?

When we checked in October 2026, a standard business seat for the main AI tools cost roughly £7 to £25 a person a month plus VAT, depending on the tool and plan, and it is sometimes included in software you already pay for. Some free versions are fine for trying things out, as long as nothing confidential goes into them.

Can we start with one person?

Yes, and it is often the best way: one willing person, one real task, then share what worked. Small successes travel.

Sources

1. Study finds ChatGPT boosts worker productivity for some writing tasks, MIT Department of Economics (Noy and Zhang, Science), July 2023.
2. Measuring the productivity impact of generative AI, National Bureau of Economic Research (Brynjolfsson, Li and Raymond), June 2023.
3. Hallucination-free? Assessing the reliability of leading AI legal research tools, Magesh and others, Stanford University, Journal of Empirical Legal Studies, 2025.
4. Large language models, small labor market effects, Humlum and Vestergaard, Becker Friedman Institute, May 2025.
5. Artificial intelligence in UK businesses: 2023 to 2026, Office for National Statistics, July 2026.
6. Business insights and impact on the UK economy: 8 October 2026, Office for National Statistics, October 2026.
7. ChatGPT and large language models: what’s the risk?, National Cyber Security Centre, March 2023.